The present invention is directed to a scene change detection system which can be used for object detection. Scene change detection is often referred to as motion conspicuity detection. While motion conspicuity detectors exist, they each have their drawbacks. Examples of such motion conspicuity detectors include variational optical flow, biological saliency, and standalone bayesian surprise. Variational optical flow was described by Bruhn, A., Weickert, J., Feddern, C., Kohlberger, T., and Schnorr, C., in “Variational optical flow computation in real time”, IEEE Transactions on Image Processing, 14(5), 608-615 (2005). Biological saliency was described by Itti, L., Koch, C., and Braun, J., in “Revisiting Spatial Vision”, Towards a Unifying Model. JOSA-A, 17(11), 1899-1917 (2000), while Standalone Bayesian Surprise was described by Itti, L., and Baldi, P. in “A principled approach to detecting surprising events in video”, Paper presented at the Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2005), and “Bayesian Surprise attracts human attention”, Paper presented at the Advances in Neural Information Processing Systems (NIPS) (2006). Each of the aforementioned conspicuity detectors, in of themselves, are incomplete for scene change detection. Further, they are subject to the effects of motion noise which dramatically decreases their efficacy.
Thus, a continuing need exists for a system that identifies regions of interest in an input frame while reducing the effect of motion noise.